Joint scheduling method based on urban public transport resources

Abstract

The invention provides a joint scheduling method based on urban public transport resources, which focuses on a bus system and a shared bicycle system, uses a reinforcement learning long-term optimal scheduling and cooperative scheduling strategy on the basis of time-space prediction, can achieve cooperative scheduling between the bus system and the shared bicycle system, solves the possible localgreedy problem, can schedule other traffic resources can be dispatched in time to meet travel requirements of users when a certain traffic service is temporarily unavailable or inapplicable. The method comprises the following steps: according to recorded crowd flow data at different time and places and people flow changes borne by various vehicles, pre-constructing a time-varying demand flow graphfor people to take the vehicles; and then, taking the current station state and the future predicted flow diagram as the state of the current system, and performing collaborative and efficient scheduling on the current multiple traffic systems by utilizing a reinforcement learning technology.

Description

Technical field [0001] The invention relates to the field of artificial intelligence, and in particular to a reinforcement learning method with a human flow prediction method and a joint dispatching of traffic resources. Background technique [0002] In recent years, traffic congestion in modern cities has increasingly become a concern for residents. As shown in the Baidu Traffic Report, the commute stress index during peak hours in Beijing reached an astonishing 1.973, resulting in longer travel times and increased vehicle queues. Previous research has shown that through rational scheduling, such as rescheduling bicycle sharing systems and optimizing bus transportation systems, transportation efficiency can be significantly improved without consuming redundant resources. [0003] The inventor found through research that there are still two shortcomings that limit the performance of the dispatching system: (1) only considering a single dispatch in a short period of time and...

AI Technical Summary

Problems solved by technology

[0003] Find through research of the present inventor, still have two shortcomings to limit the performance of dispatching system: (1) only consider the single dispatching in short time, and ignore traffic resource redistribution phenomenon after first traffic dispatching; (2) current dispatching system Only focus on one type of traffic scheduling

The multimodal nature of urban public transport is largely underutilized

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